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The purpose of this article is to explore the relationship between the attributes of Olympic mascots and their impact on sponsorship effectiveness. Based on a multiattribute model and the introduction of engagement theory and the meaning transfer model, this article uses the 2022 Beijing Winter Olympics mascot “Bing Dwen Dwen” as the research object to empirically analyze the effects and mechanisms of the mascot's attributes on preference, event engagement, sponsorship enterprise trust and sponsorship enterprise attitude, ultimately constructing a sponsorship effectiveness model.

The survey method was used to examine 238 respondents' emotions and attitudes towards companies participating in sponsoring Olympic mascots.

The study found that the main attributes of the mascot include visual and emotional factors, both of which have a positive impact on preference, with emotional factors having a greater influence than visual factors. Visual and emotional factors indirectly affect engagement through preference. Preference and engagement play a completely mediating role in the effect of mascot attributes on sponsorship enterprise trust and sponsorship enterprise attitude.

This study provides practical recommendations for managers to achieve marketing success in sports sponsorship through mascots.

This paper provides a measurement tool for the study of mascot attributes and important support for subsequent research in sponsorship marketing.

The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation.

This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises.

The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results.

By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results.

This study investigates the crucial link between sustainable practices and organizational development, focusing on sustainable knowledge management (SKM), green innovation (GI) and corporate sustainable development (CSD) in diverse Pakistani organizations.

This study employs a comprehensive research methodology involving advanced statistical techniques, such as confirmatory factor analysis, structural equation modeling and hierarchical linear modeling. These methods are instrumental in exploring the complex interrelationships between SKM, GI, moderating factors and CSD.

This research generates significant findings and actively contributes to sustainable development. The following sections (Sections 4 and 5) delve into the specific findings and in-depth discussions, shedding light on how industry regulation, organizational sustainability priorities, workplace culture collaboration and alignment between green culture and knowledge management practices influence the relationships between SKM, GI and CSD. These findings provide valuable insights for the research community and organizations striving for sustainability.

The study’s findings have practical implications for organizations seeking to enhance their sustainability efforts and embrace a socially and environmentally conscious approach to organizational growth.

This study contributes to the literature on sustainable practices and organizational development. Researchers and business people can learn a lot from it because it uses advanced econometric models in new ways and focuses on the link between knowledge management, GI and sustainable corporate development.

This paper aims to investigate how perceived working conditions affect employee performance, including safety compliance and task performance, through employee well-being (i.e. job satisfaction) in the context of the coal mining sector in China.

This paper uses the job demands-resources model to test the relationships between working conditions, including job demands (work pressure as a challenge demand and perceived risks and hazards in the workplace and ineffectiveness of the safety system as hindrance demands), job resources (interpersonal harmony), job satisfaction and performance. This study adopts a two-wave design with a three-month lag to reduce possible common method bias.

Employees who experienced high level of challenge demands, e.g. time pressure workload, reported higher levels of task performance, and this positive relationship seemed to be robust. There is a direct effect of perceived ineffectiveness of the safety system on task performance, while the relationship between perceived risks and hazards and task performance was fully mediated by job satisfaction. Challenge demands, i.e. work pressure, did not impact much on employees’ well-being, and thus job satisfaction did not mediate the relationship between work pressure and performance. Perceived ineffectiveness of the safety system was negatively associated with safety compliance. This result is not surprising since a lack of effective safety system reflects management’s ignorance of workplace safety, which demotivates employees to enact safe behaviors. In contrast, the presence and implementation of an effective safety system would be interpreted by employees as management exhibiting a high level of commitment. Work pressure was positively not negatively related to safety compliance. One possible explanation for this finding is that the effects of work pressure on safety compliance behaviors might be dependent on contextual factors such as safety climate. Interpersonal harmony moderated the relationships between work pressure and employee performance (both safety compliance and task performance) and the relationship between perceived risks and hazards and task performance, but the role of interpersonal harmony appeared more complex. There was no significant correlation between challenging job demands and individual employee performance when there were higher levels of interpersonal harmony. The relationship between perceived risks and hazards, a hindrance job demand and task performance became positive as interpersonal harmony increased but negative as interpersonal harmony decreased.

This paper provides a robust integrative theoretical framework that better explains the various types of job demands and job resources in the working environment of coal mining sector in China and their relationships to employee performance. The findings also offer valuable guidance for managers trying to identify effective ways to enhance employee performance and safety in the workplace.

This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.

This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.

Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.

The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.

This paper aims to develop a performance measurement (PM) system for fourth-party reverse logistics (RL). In this regard, it proposes simultaneous utilization of a procedural approach and hybrid use of existing performance frameworks.

The paper first describes fundamentals of RL and PM approaches in literature to build a basis for further discussion. It then carries out a systematic review of the literature on PM in RL to highlight current trends and approaches in this regard. At last, it develops a PM system for fourth-party RL by exploring relevant performance frameworks and by defining a procedure in detail.

The paper identifies the ongoing interest in development PM in RL, and the gap and the need for the development of comprehensive PM system for fourth-party RL. It also identifies the best approach is to use existing performance frameworks in literature and a procedural approach together as they complement each other rather than contradicting.

The paper fills a gap in literature by developing a comprehensive PM framework for the fourth-party RL. The presented procedure is well suited to be used as part of strategic management process in any fourth-party RL organization. It forces users a top-down approach, from strategies to measures, so that a strong linkage is established in the process. When used together with the proposed PM framework, it guarantees a comprehensive and balanced PM system.

The paper identifies the need for the development of a PM framework as well as a measurement system for the fourth-party RL in the literature. In this regard, it develops a PM framework first, and then a procedure on how to implement it. As a result, users can effectively use them as a part of strategic management process of their organizations.

The fourth-party RL is growing and very promising mode of RL for well-being of society, by offering a strong path to sustainable development in the midst of diminishing resources in the world. The existence of a well measurement system is crucial for the healthy operations and development of fourth-party RL organizations. The paper is offering a strong PM model in this regard.

The paper fulfills an identified need to study how to develop a PM system for fourth-party RL.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.